Machine Learning-Based Classification of Hypertension using CnD Features from Acceleration Photoplethysmography and Clinical Parameters.
Saad AbdullahAbdelakram HafidMaria LindénMia FolkeAnnica KristofferssonPublished in: CBMS (2023)
Keyphrases
- machine learning
- feature vectors
- classification accuracy
- feature set
- feature extraction
- machine learning approaches
- feature construction
- classification process
- feature space
- machine learning methods
- feature selection
- classification models
- pattern recognition
- machine learning algorithms
- feature analysis
- classification method
- feature generation
- extracted features
- machine learning models
- benchmark datasets
- support vector machine
- decision trees
- supervised learning
- class labels
- extracting features
- svm classification
- text classification
- support vector
- feature values
- image features
- svm classifier
- discriminative features
- supervised machine learning
- active learning
- feature ranking
- computer vision
- lung disease
- training set
- supervised classification
- bayesian methods
- weak classifiers
- feature selection algorithms
- feature subset
- high dimensionality
- information extraction
- data mining
- training data
- support vector machine svm
- unsupervised learning
- model selection
- maximum likelihood
- learning algorithm
- cardiovascular disease
- image classification